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Cross-border network for knowledge transfer and innovative development in wastewater treatment

WATERFRIENDHUSRB/1203/221/196

1st HUSRB Students Meeting

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1st Students Meeting Waterfriend

Humic substances in well-waters: Humic substances in well-waters: background and removal using background and removal using membrane filtration methodsmembrane filtration methods

Gyula VATAI,Gyula VATAI, Ildikó GALAMBOSIldikó GALAMBOS

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Corvinus University of BudapestCorvinus University of Budapest

Faculty of Food Science Faculty of Food Science Department of Food EngineeringDepartment of Food Engineering

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1st Students Meeting Waterfriend Faculties:

Food Science Horticultural Science Landscape Architecture Business Administration Social Sciences Economic Sciences

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Departments of the Faculty of Food Science

Brewing and Distilling Grain and Industrial Crop

Technology Refrigeration and Livestock Processing Technology Canning Technology Post-harvest Technology

and Sensory Laboratory

Physics and Control Applied Chemistry and

Biochemistry Food Chemistry and

Nutrition Microbiology and

Biotechnology Food Engineering Food Economy

. .


Types of Qualification BSc in Food Engineering BSc in Bioengineering

– Full time (3,5 years), part time (4,5 years) MSc in Food Safety and Quality MSc in Food Engineering

– Full and part time (2 years) PhD Degree

– Full time (3 - 5 years)– Part time (4 - 6 years)

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Bachelor in Food Engineering

Wine & Soft Drink Technology Brewing & Distilling Technology Food Preservation Technology Livestock Products Technology Industrial Crop Technology Baking and Confectionery Technology

. .


Master in Food Safety and Quality

Master in Food EngineeringFood Process EngineeringFood BiotechnologyDevelopment of Food Products and TechnologiesPost-harvest Technology and Logistic Oenology and Wine Marketing

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Food Science Doctoral School Food engineering Environmental protection Food chemistry Food quality control Biotechnology Food technologies

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Specialisation(Second Diploma, 2 years)

Master in Brewing Technology Master in Pálinka Technology Master in Wine Technology and Marketing

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1st Students Meeting Waterfriend Research topics I.

• Concentration of aroma and vitamins in fruit juices by using membrane techniques

• Optimization of the total cost of a membrane system for grape juice concentration using dynamic programming

• Experimental and numerical investigations on whey desalination with nanofiltrration/diafiltration

• Wine filtration in order to decrease the alcohol content• Recovery of aroma compounds from fruit juices by

pervaporation• Dewatering alcohol by pervaporation

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Research topics II.• Elimination of pollutants from drinking water resources

by using nano- or ultrafiltration• Air/gas cleaning by using membrane absorption and

desorption and conventional absorption • Treating industrial wastewater by using nanofiltration

and/or membrane distillation and/or pervaporation• Treating and recycling CIP water by combined filtration

methods • Separation of stable oil-water emulsion by nano- and

ultrafiltration• Cross-flow membrane emulsification

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CFD and laboratory analysis of axial cross-flow velocity in CFD and laboratory analysis of axial cross-flow velocity in porous tube packed with differently structured static porous tube packed with differently structured static mixersmixers

• Porous tube as an ultrafiltration membrane filter made from zirconium-oxide which is very effective in the separation of stable oil-in-water microemulsions, especially when the tube is filled with static mixer.

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• Computational fluid dynamics (CFD) was used for modelling flow regime in a porous tube.

• The results of the CFD analysis were used in the optimisation of the static mixer’s geometry since it has significant effect the energy requirement of this advanced membrane technology.

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Input:3D MATRIX CFD

Output:3D MATRIX

Visualization usingParaview

(open source prog.)

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Resultof

CFD

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The static mixers developed in cooperation with FTUNS were tested “in vitro” from the aspect of separation quality and process productivity as well to validate CFD results and to develop a cost effective, green method to recover oily wastewaters for sustainable development

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Experiments with manufactured static mixers - FLUXES

Initial flux, RFR on TMP 2 bar

050

100150

200250300

350400

450500

50 100 150

RFR (L h-1)

Flux

(L m

-2h-1

)

No S.M.

1

2

34

5

6

Initial flux, TMP on 100 l/h

0

100

200

300

400

500

600

1 2 3TMP (bar)

Flux

(L m

-2 h

-1) No

S.M.1

2

3

4

5

6

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Experiments with manufactured static mixers – PRESSURE DROP

Pressure drop, RFR on TMP 2 bar

0.0

0.5

1.0

1.5

2.0

2.5

50 100 150

RFR (L h-1)

Pres

sure

dro

p (b

ar)

No S.M.

1

2

34

5

6

Pressure drop, TMP on 100 l/h

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1 2 3TMP (bar)

Pres

sure

dro

p (b

ar) No

S.M.1

2

3

4

5

6

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Experiments with manufactured static mixers - RETENTION

Retention %, RFR on TMP 2 bar

505560

6570758085

9095

100

50 100 150

RFR (L h-1)

R %

No S.M.

1

2

34

5

6

Retention %, TMP on 100 l/h

50

55

60

65

7075

80

85

90

95

100

1 2 3TMP (bar)

R %

NoS.M.1

2

3

4

5

6

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Drinking water quality requirements201/2001. (X. 25.) executive decreeHumic substances (HS): no limit value

Trihalomethans: 50 g/L HS calculated from trihalomethans: ~3,5 mg/L

Arsenic: 50 g/L – 10 g/LRemoval of

Micro-organismVolatile and non-volatile organic substances (VOC, humic substances)Heavy-metals, metal-ions (Fe, Mn, As)Pesticides, insecticides

Introduction

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Appearance of humic acid and arsenic in drinking water (Hungary)

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Removal of humic substances from model-solution and well-waters

Definition: The humic substances are faintly acidic macromolecular conglomerations, coloured from yellowish to dark brown.

Adverse to health: carcinogenic substances (trihalomethans) are the by-products of the reactions between the water clarifying antiseptics and the dissolved organic components.

Structure of humic substances:Molecular weight: 1500-20000 g/molDifferent size and structureSensitive for external manipulation, difficult to fractionate

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Removal of humic substances

• Traditional methods: • Coagulation and flocculation• Activated carbon• Ion exchange

• Membrane separation: advatages: no carcinogenic by-product, closed system, easy for control, good quality of the drinking water

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Aim: membrane screening and membrane selection for humic acid solutionMaterials: Humic acid model solution (producer: Sigma-Aldrich,

conc. 10 mg/L) Well-waters containing humic acid derived from

Hungary and from SerbiaAnalysis: UV absorbance (254 nm)

TOC (mg/L) (Total Organic Carbon)DOC (mg/L) (Dissolved Organic Carbon)

Membranes: Flat sheet and hollow-fiber membranes, MWCO: 100-0.3 kDa

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MaterialsLaboratory tests

Model solution (humic acid, deionized water)Well waters from:

Zenta (Serbia)Békéscsaba, Orosháza, Gyula, Kondoros (Hungary)

Pilot experimentsWell water (high arsenic and humic acid concentration,

Békéscsaba, Hungary)

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1st Students Meeting Waterfriend Applied membranes

Membrane

Producer Material KialakításaMWCO

(kDa)

Pure water flux

(L m-2h-1)

(T=25 °C)Code Type

UF M1 BFM–70100 Berghof Polyether-sulfon (PES) flat-sheet 100 222,2*

UF M2 SP 015 A Zoltec Polyether-sulfon (PES) flat-sheet 15 213,6*

UF M3 SP 006 A Zoltec Polyether-sulfon (PES) flat-sheet 6 191,5*

UF M4 BFM–3705 BerghofPoly-aril-ether-keton

(PAES)flat-sheet 5 76,1*

UF M5 PM2 Koch Polysulfon(PS) hollow-fiber 2 50,2**

UF M6 PM1 Koch Polysulfon (PS) hollow-fiber 1 41,0**

NF M7 NF 200 Dow/Filmtec Polyamide (PA) flat-sheet 0,4 84***

NF M8 NF 45 Dow/Filmtec Polyamide (PA) flat-sheet 0,3 55***

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The schematic diagram of the laboratory equipment

vessel

pump

membrane rotameter

permeate

TI

PI PI

samples

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The schematic diagram of the pilot-equipment

Permeate

RotameterFeed

AC Pre-filter

Membrane

Recycle

Permeate

Concentrate

PI

Pump

PI

C R P

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The picture of the laboratory ( self made hollow fiber) and pilot-The picture of the laboratory ( self made hollow fiber) and pilot-equipment ( industrial hollow fiber module)equipment ( industrial hollow fiber module)

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The humic substance concentration in model-solutions (p = 4 bar, QR = 400 L/h)

Feed M1 M2 M3 M4Abs

DOCTOC

0

2

4

6

8

10

12

HS

conc

entr

atio

n (m

g/L

)

Comparison of the humic-substance concentration in well-water (Zenta) and model-solution (p = 4 bar, QR= 260 L/h, UV254nm)

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Filtration of model-solution, PM1 and PM2 (1 and 2 kDa)

Filtration of well-water (Zenta), PM1 and PM2 (1 and 2 kDa)

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Cost-evaluation Initial data:

Karcag town, 40,000 inhabitants 230 L/inhabitant/day drinking-water requirement 27 days operation mounthly 10,000 m3/day water-requirement Investment and operational costs based on 2004. data

Membrane-surface (NF) : A = Jvíz / Jszűrlet*Kh =16700 m2

450 pieces of 8 inch diam. membrane module

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ConclusionsLaboratory tests

Filtration of humic substances the rejection on UF membranes was ~80-90 %

by model-solutions, ~65-70 % by well-wateron NF membranes ~100 %The rejection of M5-M6 membranes (1 és 2

kDa) was proper for well-water, the HS concentration < 3,5mg/L

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Presentation/lecture has been produced with the financial assistance of the European Union. The content of the presentation/lecture is the sole responsibility of University of Novi Sad, Faculty of Technology and can under

no circumstances be regarded as reflecting the position of the European Union and/or the Managing Authority.

Special thanks to my hard-working and cooperative staff of the Department:

Erika Békássy-Molnár - Prof. Emerita

Edit Márki , András Koris, Zoltán Kovács - Associate Professors

Szilvia Bánvölgyi, Ildikó Galambos, Eszter Fogarassy - Assistant Professors

Nelli Kőszegi, Igor Gáspár, Gábor Rácz - Assistant Lecturers

PhD Students: Krisztina Albert, Balázs Verasztó, Máté András Molnárand further MSc and BSc students

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Optimization of the total cost of a membrane system for grape juice concentration using dynamic programming

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The flow diagram of the technology

The microfiltration served for clarification only, therefore this constant cost could be omitted from the point of view of optimization

pRO

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1st Students Meeting Waterfriend Investment + operation cost of NF in function of the NF input concentration

Membrane cost ~ Am0,821Energy prices: up to date energy costWorking days 300 day /yearWorking hours 8 h/day

Investment + operation cost of RO in function of the RO output

concentration

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1st Students Meeting Waterfriend Total cost = cost of NF+cost of RO

7900

8000

8100

8200

8300

8400

8500

8600

10 15 20 25 30 35 40 45x1 concentration (ºBrix)

Opt

imal to

tal c

ost (

EUR/yea

r)

Optimal operation parameters:

1. RO transmembrane pressure 64 bar2. NF transmembrane pressure 70 bar3. x1 concentration between RO and NF: 24,5 Brix

Processed grape juice: 1500 liter/h

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EXPERIMENTAL AND NUMERICAL INVESTIGATIONS ON WHEY EXPERIMENTAL AND NUMERICAL INVESTIGATIONS ON WHEY DESALINATION WITH NANOFILTRATIONDESALINATION WITH NANOFILTRATION/DIAFILTRATION/DIAFILTRATION

This research work investigates robust data-driven mode-ling techniques to predict the dynamics of whey nanofiltration/diafiltration.We investigated statistical tools, such as: •Response surface methodology (RSM) and •Partial least-squares regression (PLSR), •Machine learning techniques in order to estimate the dependence of flux and rejections on the feed composition

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ORGANIC COMPOUNDS (LEFT SIDE) AND IONIC SPECIES ORGANIC COMPOUNDS (LEFT SIDE) AND IONIC SPECIES (RIGHT SIDE) AS FUNCTION OF OPERATIONAL TIME FOR (RIGHT SIDE) AS FUNCTION OF OPERATIONAL TIME FOR

VARIABLE-VOLUME DIAFILTRATION WITH VARIABLE-VOLUME DIAFILTRATION WITH αα=0.75.=0.75.

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SIMULATION OF THE DYNAMICS OF SWEET WHEY DIAFILTRATION WITH SIMULATION OF THE DYNAMICS OF SWEET WHEY DIAFILTRATION WITH ARTIFICIAL NEURAL NETWORK APPROACH. PERMEATE FLUX VS ARTIFICIAL NEURAL NETWORK APPROACH. PERMEATE FLUX VS OPERATIONAL TIME (LEFT SIDE); CONDUCTIVITY AND LACTOSE OPERATIONAL TIME (LEFT SIDE); CONDUCTIVITY AND LACTOSE

CONCENTRATION AS FUNCTION OF VOLUME CONCENTRATION FACTOR CONCENTRATION AS FUNCTION OF VOLUME CONCENTRATION FACTOR (RIGHT SIDE). (RIGHT SIDE).

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Recovery of aroma compounds from fruit juices by Recovery of aroma compounds from fruit juices by pervaporationpervaporation

Concentration by evaporationAroma recovery with distillation columnsApplicability of pervaporationStudied fruit juices: apple, pineapple, raspberry

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Modelling of pervaporation by SuperPro Designer Modelling of pervaporation by SuperPro Designer softwaresoftware

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